Adaptive engagement in smart tourism: a context-sensitive multi-condition model for older adults

Yingying Chen et al.

Journal of Hospitality and Tourism Technology2026https://doi.org/10.1108/jhtt-05-2025-0395article
AJG 1ABDC B
Weight
0.50

Abstract

Purpose This study aims to develop a theoretical model to explain how older adults engage with smart tourism services by examining five key conditions: user-related, technological, tourism-specific, social mechanisms and experiential feedback. It aims to capture the adaptive strategies older adults adopt in navigating digital tourism environments. Design/methodology/approach Using a grounded theory approach, this study conducted 50 in-depth interviews with older Chinese adults (users and non-users). Theoretical sampling guided data collection and open, axial and selective coding generated a context-sensitive multi-condition adaptation engagement model. Findings The model reveals that engagement behavior emerges from dynamic interactions among the five condition clusters. These interactions generate three adaptive outcomes: active use, limited use and non-use. Social support, norms, economic incentives and feedback from prior experiences serve as key mechanisms moderating these trajectories. Originality/value By integrating structural, social and experiential factors, this model extends beyond conventional technology adoption frameworks (e.g. technology acceptance model, unified theory of acceptance and use of technology), offering a comprehensive understanding of older adults’ digital engagement in tourism. It provides conceptual and practical insights for designing age-inclusive smart tourism services and policies that respond to the lived realities of aging users.

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https://doi.org/https://doi.org/10.1108/jhtt-05-2025-0395

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@article{yingying2026,
  title        = {{Adaptive engagement in smart tourism: a context-sensitive multi-condition model for older adults}},
  author       = {Yingying Chen et al.},
  journal      = {Journal of Hospitality and Tourism Technology},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/jhtt-05-2025-0395},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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